Data Source

Source: Low-Income Energy Affordability Data, 2018 Update

About the Data

The US Department of Energy’s Low-Income Energy Affordability Data (LEAD) shows energy expenditures and energy burdens for households. This particular data, pulled from the 2018 Area Median Income data, also breaks households into income brackets. The income brackets are as a percentage of the area’s median income (AMI), where 100% indicates that household income is equivalent to the AMI. The income brackets in this data are 0-30%, 30-60%, 60-80%, 80-100%, and 100%+.

Variable Descriptions

glimpse(lead)
## Rows: 11
## Columns: 39
## $ FIP                      <dbl> 51001090100, 51001090200, 51001090300, 510010…
## $ state_fip                <dbl> 51, 51, 51, 51, 51, 51, 51, 51, 51, 51, 51
## $ county_fip               <chr> "001", "001", "001", "001", "001", "001", "00…
## $ tract_fip                <chr> "090100", "090200", "090300", "090400", "0905…
## $ county                   <chr> "Accomack", "Accomack", "Accomack", "Accomack…
## $ totalinc                 <dbl> 106773487, 129612461, 61442032, 120047897, 53…
## $ totalelep                <dbl> 6143964, 6615628, 2167116, 4461609, 2081862, …
## $ totalgas                 <dbl> 955390.4, 2182387.7, 709611.5, 1232994.8, 731…
## $ totalother               <dbl> 321101.4, 516012.6, 311333.1, 410918.6, 43256…
## $ averageburden            <dbl> 6.949718, 7.186059, 5.188728, 5.085905, 6.031…
## $ avg_hh_exp               <dbl> 4748.120, 3657.473, 3077.275, 3053.370, 3110.…
## $ lowburden                <dbl> 683.9598, 1096.5446, 440.7706, 1058.9761, 462…
## $ highburden               <dbl> 184.2558, 483.4608, 194.3784, 394.9814, 157.6…
## $ veryhighburden           <dbl> 341.3380, 634.9627, 208.8109, 400.2121, 180.2…
## $ extremelyhighburden      <dbl> 291.1445, 300.4294, 149.9686, 201.2892, 200.1…
## $ totalunits               <dbl> 1500.6981, 2515.3974, 993.9284, 2055.4588, 10…
## $ numberburdened           <dbl> 816.7382, 1418.8528, 553.1579, 996.4827, 538.…
## $ percentburdened          <dbl> 54.42389, 56.40671, 55.65369, 48.47982, 53.78…
## $ total_0_30               <dbl> 167.4056, 263.7055, 186.7433, 309.1969, 202.3…
## $ total_30_60              <dbl> 182.5965, 390.5556, 153.4957, 391.8459, 155.7…
## $ total_60_80              <dbl> 136.92566, 366.98719, 144.03470, 238.49260, 9…
## $ total_80_100             <dbl> 161.44690, 327.18867, 96.45968, 161.76691, 93…
## $ total_over_100           <dbl> 852.3234, 1166.9604, 413.1950, 954.1566, 453.…
## $ burdened_0_30            <dbl> 167.4056, 263.7055, 186.7433, 304.8229, 202.3…
## $ burdened_30_60           <dbl> 182.5965, 369.1552, 151.0950, 366.3732, 154.2…
## $ burdened_60_80           <dbl> 135.96044, 324.84586, 129.60361, 174.95300, 8…
## $ burdened_80_100          <dbl> 157.32611, 280.91965, 58.84603, 98.76576, 67.…
## $ burdened_over_100        <dbl> 173.44962, 180.22663, 26.86993, 51.56778, 28.…
## $ percent_0_30             <dbl> 100.00000, 100.00000, 100.00000, 98.58538, 10…
## $ percent_30_60            <dbl> 100.00000, 94.52052, 98.43594, 93.49933, 99.0…
## $ percent_60_80            <dbl> 99.29508, 88.51695, 89.98083, 73.35783, 88.88…
## $ percent_80_100           <dbl> 97.44759, 85.85861, 61.00583, 61.05437, 72.21…
## $ percent_over_100         <dbl> 20.350211, 15.444108, 6.502966, 5.404541, 6.3…
## $ total_owners             <dbl> 1160.5645, 1820.6219, 676.0099, 1180.9014, 64…
## $ total_renters            <dbl> 349.7431, 696.1272, 318.2414, 889.5201, 359.8…
## $ burdened_owners          <dbl> 529.8751, 949.5822, 317.8923, 478.9872, 286.2…
## $ burdened_renters         <dbl> 286.8631, 469.2706, 235.2655, 517.4956, 251.8…
## $ percent_burdened_owners  <dbl> 45.65667, 52.15702, 47.02481, 40.56115, 44.68…
## $ percent_burdened_renters <dbl> 82.02109, 67.41163, 73.92675, 58.17694, 69.98…
meta %>% 
  mutate(label = paste0(varname, ": ", about)) %>% 
  select(label) %>% 
  as.list()
## $label
##  [1] "FIP: 11-digit FIPS code (State, County, Tract)"                                                                                                        
##  [2] "state_fip: 2-digt State FIPS code"                                                                                                                     
##  [3] "county_fip: 3-digit County FIPS code"                                                                                                                  
##  [4] "tract_fip: 6-digit Tract FIPS code"                                                                                                                    
##  [5] "county: County name"                                                                                                                                   
##  [6] "totalinc: Aggregated income for the entire census tract"                                                                                               
##  [7] "totalelep: Aggregated electric expenditures for the entire census tract"                                                                               
##  [8] "totalgas: Aggregated gas expenditures for the entire census tract"                                                                                     
##  [9] "totalother: Aggregated other energy expenditures for the entire census tract"                                                                          
## [10] "averageburden: Average household energy burden; energy burden is defined as the percent of income spent on energy"                                     
## [11] "avg_hh_exp: Average household yearly expenditure on electric + gas + other energy"                                                                     
## [12] "lowburden: Number of households with less than 6% energy burden"                                                                                       
## [13] "highburden: Number of households with 6-10% energy burden"                                                                                             
## [14] "veryhighburden: Number of households with 10-20% energy burden"                                                                                        
## [15] "extremelyhighburden: Number of households with greater than 20% energy burden"                                                                         
## [16] "totalunits: Total number of housing units in the census tract"                                                                                         
## [17] "numberburdened: Burdened households are those that bear at least a 6% energy burden (fall in the high, very high, or extremely high burden categories)"
## [18] "percentburdened: Percent of households that are energy burdened (numberburdened/totalunits)"                                                           
## [19] "total_0_30: Number of households with incomes that are 0-30% of the Area Median Income"                                                                
## [20] "total_30_60: Number of households with incomes that are 30-60% of the Area Median Income"                                                              
## [21] "total_60_80: Number of households with incomes that are 60-80% of the Area Median Income"                                                              
## [22] "total_80_100: Number of households with incomes that are 80-100% of the Area Median Income"                                                            
## [23] "total_over_100: Number of households with incomes that are more than 100% of the Area Median Income"                                                   
## [24] "burdened_0_30: Number of households in the 0-30% AMI range that are energy burdened"                                                                   
## [25] "burdened_30_60: Number of households in the 30-60% AMI range that are energy burdened"                                                                 
## [26] "burdened_60_80: Number of households in the 60-80% AMI range that are energy burdened"                                                                 
## [27] "burdened_80_100: Number of households in the 80-100% AMI range that are energy burdened"                                                               
## [28] "burdened_over_100: Number of households in the 100%+ AMI range that are energy burdened"                                                               
## [29] "percent_0_30: Percent of households in the 0-30% AMI range that are energy burdened (burdened_0_30/total_0_30)"                                        
## [30] "percent_30_60: Percent of households in the 30-60% AMI range that are energy burdened (burdened_30_60/total_30_60)"                                    
## [31] "percent_60_80: Percent of households in the 60-80% AMI range that are energy burdened (burdened_60_80/total_60_80)"                                    
## [32] "percent_80_100: Percent of households in the 80-100% AMI range that are energy burdened (burdened_80_100/total_80_100)"                                
## [33] "percent_over_100: Percent of households in the 100%+ AMI range that are energy burdened (burdened_over_100/total_over_100)"                            
## [34] "total_owners: Total number of households that are owned in the census tract"                                                                           
## [35] "total_renters: Total number of households that are rented in the census tract"                                                                         
## [36] "burdened_owners: Number of owned households that are energy burdened"                                                                                  
## [37] "burdened_renters: Number of rented households that are energy burdened"                                                                                
## [38] "percent_burdened_owners: Percent of owned households that are energy burdened (burdened_owners/total_owners)"                                          
## [39] "percent_burdened_renters: Percent of rented households that are energy burdened (burdened_renters/total_renters)"

Summaries

Summary of all non-missing variables:

lead %>% select(-c(FIP:county)) %>% 
  select(where(~is.numeric(.x) && !is.na(.x))) %>% 
  as.data.frame() %>% 
  stargazer(., type = "text", title = "Summary Statistics", digits = 1,
            summary.stat = c("mean", "sd", "min", "median", "max"))
## 
## Summary Statistics
## ===========================================================================================
## Statistic                    Mean       St. Dev.       Min         Median          Max     
## -------------------------------------------------------------------------------------------
## totalinc                 99,792,683.0 26,921,352.0 53,813,976.0 106,773,487.0 129,612,461.0
## totalelep                3,984,222.0  1,430,540.0  2,081,862.0   3,807,970.0   6,615,628.0 
## totalgas                 1,098,016.0   430,572.4    709,611.5     955,390.4    2,182,388.0 
## totalother                404,038.2     87,880.4    307,947.2     399,768.1     544,452.8  
## averageburden                5.5          0.9          4.6           5.2           7.2     
## avg_hh_exp                 3,263.6       547.9       2,711.9       3,107.8       4,748.1   
## lowburden                   858.3        257.7        440.8         957.0        1,140.5   
## highburden                  261.2        103.9        157.6         234.1         483.5    
## veryhighburden              314.8        124.8        180.2         289.6         635.0    
## extremelyhighburden         221.8         53.1        143.5         231.9         300.4    
## totalunits                 1,656.2       454.6        993.9        1,788.0       2,515.4   
## numberburdened              797.9        248.6        538.1         774.7        1,418.9   
## percentburdened              48.5         6.4          39.1         48.5          56.4     
## total_0_30                  235.8         50.4        167.4         244.8         309.2    
## total_30_60                 239.9         85.3        153.5         196.9         391.8    
## total_60_80                 187.1         80.6         95.6         149.1         367.0    
## total_80_100                168.7         62.5         93.4         161.6         327.2    
## total_over_100              824.8        241.2        413.2         868.9        1,167.0   
## burdened_0_30               234.1         48.7        167.4         244.8         306.9    
## burdened_30_60              230.1         76.4        151.1         196.5         369.2    
## burdened_60_80              159.6         69.7         85.0         137.4         324.8    
## burdened_80_100             119.9         62.1         58.8         98.8          280.9    
## burdened_over_100            54.2         61.5         14.8         29.0          180.2    
## percent_0_30                 99.4         1.6           95           100           100     
## percent_30_60                96.6         3.0           92          96.3           100     
## percent_60_80                85.7         9.7          65.4         88.5          99.3     
## percent_80_100               69.1         13.0         56.8         63.8          97.4     
## percent_over_100             6.4          6.1          1.5           4.9          20.4     
## total_owners               1,129.8       337.3        640.5        1,160.6       1,820.6   
## total_renters               533.0        173.3        318.2         499.0         889.5    
## burdened_owners             472.4        179.1        286.2         461.5         949.6    
## burdened_renters            325.4         93.3        235.3         286.9         517.5    
## percent_burdened_owners      41.8         6.2          31.9         42.7          52.2     
## percent_burdened_renters     62.6         10.0         51.2         61.0          82.0     
## -------------------------------------------------------------------------------------------

Visual Distributions

Visual distributions of the data, shown with histograms and scatterplots

Spatial Distributions

Key Outcomes

Maps to show the distribution of variables across spatial units

Average Energy Burden

pal <- colorNumeric("Blues", reverse = TRUE, domain = easternshapes$averageburden)

leaflet(easternshapes) %>%
  addProviderTiles("CartoDB.Positron") %>%
  addPolygons(data = easternshapes,
              fillColor = ~pal(averageburden),
              weight = 1,
              opacity = 1,
              color = "white",
              fillOpacity = 0.6,
              highlight = highlightOptions(weight = 2, fillOpacity = 0.8, bringToFront = T),
              popup = paste0("Tract Number: ", easternshapes$tract, "<br>",
                             "Avg. Burden: ", round(easternshapes$averageburden, 2))) %>%
  addLegend("bottomright", pal = pal, values = easternshapes$averageburden,
            title = "Average Energy Burden", opacity = 0.7)

Average Yearly Household Energy Expenditures

pal <- colorNumeric("Blues", reverse = FALSE, domain = easternshapes$avg_hh_exp)

leaflet(easternshapes) %>%
  addProviderTiles("CartoDB.Positron") %>%
  addPolygons(data = easternshapes,
              fillColor = ~pal(avg_hh_exp),
              weight = 1,
              opacity = 1,
              color = "white",
              fillOpacity = 0.6,
              highlight = highlightOptions(weight = 2, fillOpacity = 0.8, bringToFront = T),
              popup = paste0("Tract Number: ", easternshapes$tract, "<br>",
                             "Avg. Household Energy Expenditures: ", round(easternshapes$avg_hh_exp, 2))) %>%
  addLegend("bottomright", pal = pal, values = easternshapes$avg_hh_exp,
            title = "Average Yearly Household Energy Expenditures", opacity = 0.7)

Number of Energy Burdened Households

pal <- colorNumeric("Blues", reverse = FALSE, domain = easternshapes$numberburdened)

leaflet(easternshapes) %>%
  addProviderTiles("CartoDB.Positron") %>%
  addPolygons(data = easternshapes,
              fillColor = ~pal(numberburdened),
              weight = 1,
              opacity = 1,
              color = "white",
              fillOpacity = 0.6,
              highlight = highlightOptions(weight = 2, fillOpacity = 0.8, bringToFront = T),
              popup = paste0("Tract Number: ", easternshapes$tract, "<br>",
                             "Number Burdened: ", round(easternshapes$numberburdened, 2))) %>%
  addLegend("bottomright", pal = pal, values = easternshapes$numberburdened,
            title = "Number of Energy Burdened Households", opacity = 0.7)

Percent of Energy Burdened Households

All AMI Levels

pal <- colorNumeric("Blues", reverse = FALSE, domain = easternshapes$percentburdened)

leaflet(easternshapes) %>%
  addProviderTiles("CartoDB.Positron") %>%
  addPolygons(data = easternshapes,
              fillColor = ~pal(percentburdened),
              weight = 1,
              opacity = 1,
              color = "white",
              fillOpacity = 0.6,
              highlight = highlightOptions(weight = 2, fillOpacity = 0.8, bringToFront = T),
              popup = paste0("Tract Number: ", easternshapes$tract, "<br>",
                            "Pct. Burdened: ", round(easternshapes$percentburdened, 2))) %>%
  addLegend("bottomright", pal = pal, values = easternshapes$percentburdened,
            title = "Percent of Energy Burdened Households", opacity = 0.7)

0-30% AMI

pal <- colorNumeric("Blues", reverse = FALSE, domain = easternshapes$percent_0_30)

leaflet(easternshapes) %>%
  addProviderTiles("CartoDB.Positron") %>%
  addPolygons(data = easternshapes,
              fillColor = ~pal(percent_0_30),
              weight = 1,
              opacity = 1,
              color = "white",
              fillOpacity = 0.6,
              highlight = highlightOptions(weight = 2, fillOpacity = 0.8, bringToFront = T),
              popup = paste0("Tract Number: ", easternshapes$tract, "<br>",
                            "Pct. Burdened - 0-30% AMI: ", round(easternshapes$percent_0_30, 2))) %>%
  addLegend("bottomright", pal = pal, values = easternshapes$percent_0_30,
            title = "Percent of Energy Burdened Households", opacity = 0.7)

30-60% AMI

pal <- colorNumeric("Blues", reverse = FALSE, domain = easternshapes$percent_30_60)

leaflet(easternshapes) %>%
  addProviderTiles("CartoDB.Positron") %>%
  addPolygons(data = easternshapes,
              fillColor = ~pal(percent_30_60),
              weight = 1,
              opacity = 1,
              color = "white",
              fillOpacity = 0.6,
              highlight = highlightOptions(weight = 2, fillOpacity = 0.8, bringToFront = T),
              popup = paste0("Tract Number: ", easternshapes$tract, "<br>",
                            "Pct. Burdened - 30-60% AMI: ", round(easternshapes$percent_30_60, 2))) %>%
  addLegend("bottomright", pal = pal, values = easternshapes$percent_30_60,
            title = "Percent of Energy Burdened Households", opacity = 0.7)

60-80% AMI

pal <- colorNumeric("Blues", reverse = FALSE, domain = easternshapes$percent_60_80)

leaflet(easternshapes) %>%
  addProviderTiles("CartoDB.Positron") %>%
  addPolygons(data = easternshapes,
              fillColor = ~pal(percent_60_80),
              weight = 1,
              opacity = 1,
              color = "white",
              fillOpacity = 0.6,
              highlight = highlightOptions(weight = 2, fillOpacity = 0.8, bringToFront = T),
              popup = paste0("Tract Number: ", easternshapes$tract, "<br>",
                            "Pct. Burdened - 60-80% AMI: ", round(easternshapes$percent_60_80, 2))) %>%
  addLegend("bottomright", pal = pal, values = easternshapes$percent_60_80,
            title = "Percent of Energy Burdened Households", opacity = 0.7)

80-100% AMI

pal <- colorNumeric("Blues", reverse = FALSE, domain = easternshapes$percent_80_100)

leaflet(easternshapes) %>%
  addProviderTiles("CartoDB.Positron") %>%
  addPolygons(data = easternshapes,
              fillColor = ~pal(percent_80_100),
              weight = 1,
              opacity = 1,
              color = "white",
              fillOpacity = 0.6,
              highlight = highlightOptions(weight = 2, fillOpacity = 0.8, bringToFront = T),
              popup = paste0("Tract Number: ", easternshapes$tract, "<br>",
                            "Pct. Burdened - 80-100% AMI: ", round(easternshapes$percent_80_100, 2))) %>%
  addLegend("bottomright", pal = pal, values = easternshapes$percent_80_100,
            title = "Percent of Energy Burdened Households", opacity = 0.7)

100%+ AMI

pal <- colorNumeric("Blues", reverse = FALSE, domain = easternshapes$percent_over_100)

leaflet(easternshapes) %>%
  addProviderTiles("CartoDB.Positron") %>%
  addPolygons(data = easternshapes,
              fillColor = ~pal(percent_over_100),
              weight = 1,
              opacity = 1,
              color = "white",
              fillOpacity = 0.6,
              highlight = highlightOptions(weight = 2, fillOpacity = 0.8, bringToFront = T),
              popup = paste0("Tract Number: ", easternshapes$tract, "<br>",
                            "Pct. Burdened - 100%+ AMI: ", round(easternshapes$percent_over_100, 2))) %>%
  addLegend("bottomright", pal = pal, values = easternshapes$percent_over_100,
            title = "Percent of Energy Burdened Households", opacity = 0.7)

Percent of Energy Burdened Renters/Owners

Renters

pal <- colorNumeric("Blues", reverse = FALSE, domain = easternshapes$percent_burdened_renters)

leaflet(easternshapes) %>%
  addProviderTiles("CartoDB.Positron") %>%
  addPolygons(data = easternshapes,
              fillColor = ~pal(percent_burdened_renters),
              weight = 1,
              opacity = 1,
              color = "white",
              fillOpacity = 0.6,
              highlight = highlightOptions(weight = 2, fillOpacity = 0.8, bringToFront = T),
              popup = paste0("Tract Number: ", easternshapes$tract, "<br>",
                             "Pct. of Renters Burdened: ", round(easternshapes$percent_burdened_renters, 2))) %>%
  addLegend("bottomright", pal = pal, values = easternshapes$percent_burdened_renters,
            title = "Percent of Energy Burdened Rented Households", opacity = 0.7)

Owners

pal <- colorNumeric("Blues", reverse = FALSE, domain = easternshapes$percent_burdened_owners)

leaflet(easternshapes) %>%
  addProviderTiles("CartoDB.Positron") %>%
  addPolygons(data = easternshapes,
              fillColor = ~pal(percent_burdened_owners),
              weight = 1,
              opacity = 1,
              color = "white",
              fillOpacity = 0.6,
              highlight = highlightOptions(weight = 2, fillOpacity = 0.8, bringToFront = T),
              popup = paste0("Tract Number: ", easternshapes$tract, "<br>",
                             "Pct. of Owners Burdened: ", round(easternshapes$percent_burdened_owners, 2))) %>%
  addLegend("bottomright", pal = pal, values = easternshapes$percent_burdened_owners,
            title = "Percent of Energy Burdened Owned Households", opacity = 0.7)